We investigate the problem of recognizing words from\ud video, fingerspelled using the British Sign Language (BSL)\ud fingerspelling alphabet. This is a challenging task since the\ud BSL alphabet involves both hands occluding each other, and\ud contains signs which are ambiguous from the observer’s\ud viewpoint. The main contributions of our work include:\ud (i) recognition based on hand shape alone, not requiring\ud motion cues; (ii) robust visual features for hand shape\ud recognition; (iii) scalability to large lexicon recognition\ud with no re-training.\ud We report results on a dataset of 1,000 low quality webcam\ud videos of 100 words. The proposed method achieves a\ud word recognition accuracy of 98.9%
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.